Because right now the major reason people still deny LLM as "intelligent" is because it has no connection or understanding to the things it is saying. You can make it say 1+1=2 but it inherently does not have a real concept of what is one thing and what are two things. Its neural network just perceived the weights to give the most statistically correct answer based on what it was modeled on, i.e. text.

So instead of training it that way, the network can potentially be trained to "perceive" or "model" the reality beyond the digital world. The only way we know or have enough experience and data to do so is through our own experience. An embodied AI is what I think is required for anything to actually grasp the real concepts, or at least as close as possible to them.

And without that inherent understanding, no matter how useful a model is, it will never be a "general" inteligence.